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title: DALL·E mini | |
emoji: 🥑 | |
colorFrom: yellow | |
colorTo: green | |
sdk: streamlit | |
app_file: app/app.py | |
pinned: false | |
# DALL·E Mini | |
_Generate images from a text prompt_ | |
<img src="img/logo.png" width="200"> | |
Our logo was generated with DALL·E mini using the prompt "logo of an armchair in the shape of an avocado". | |
You can create your own pictures with [the demo](https://huggingface.co/spaces/flax-community/dalle-mini). | |
## How does it work? | |
Refer to [our report](https://wandb.ai/dalle-mini/dalle-mini/reports/DALL-E-mini--Vmlldzo4NjIxODA). | |
## Development | |
### Dependencies Installation | |
The root folder and associated [`requirements.txt`](./requirements.txt) is only for the app. | |
For development, use [`dev/requirements.txt`](dev/requirements.txt) or [`dev/environment.yaml`](dev/environment.yaml). | |
### Training of VQGAN | |
The VQGAN was trained using [taming-transformers](https://github.com/CompVis/taming-transformers). | |
We recommend using the latest version available. | |
### Conversion of VQGAN to JAX | |
Use [patil-suraj/vqgan-jax](https://github.com/patil-suraj/vqgan-jax). | |
### Training of Seq2Seq | |
Refer to [`dev/seq2seq`](dev/seq2seq) folder. | |
You can also adjust the [sweep configuration file](https://docs.wandb.ai/guides/sweeps) if you need to perform a hyperparameter search. | |
### Inference Pipeline | |
To generate sample predictions and understand the inference pipeline step by step, refer to [`dev/inference/inference_pipeline.ipynb`](dev/inference/inference_pipeline.ipynb). | |
[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/borisdayma/dalle-mini/blob/main/dev/inference/inference_pipeline.ipynb) | |
## FAQ | |
### Where to find the latest models? | |
Trained models are on 🤗 Model Hub: | |
- [VQGAN-f16-16384](https://huggingface.co/flax-community/vqgan_f16_16384) for encoding/decoding images | |
- [DALL·E mini](https://huggingface.co/flax-community/dalle-mini) for generating images from a text prompt | |
### Where does the logo come from? | |
The "armchair in the shape of an avocado" was used by OpenAI when releasing DALL·E to illustrate the model's capabilities. Having successful predictions on this prompt represents a big milestone to us. | |
## Authors | |
- [Boris Dayma](https://github.com/borisdayma) | |
- [Suraj Patil](https://github.com/patil-suraj) | |
- [Pedro Cuenca](https://github.com/pcuenca) | |
- [Khalid Saifullah](https://github.com/khalidsaifullaah) | |
- [Tanishq Abraham](https://github.com/tmabraham) | |
- [Phúc Lê Khắc](https://github.com/lkhphuc) | |
- [Luke Melas](https://github.com/lukemelas) | |
- [Ritobrata Ghosh](https://github.com/ghosh-r) | |
## Acknowledgements | |
- 🤗 Hugging Face for organizing [the FLAX/JAX community week](https://github.com/huggingface/transformers/tree/master/examples/research_projects/jax-projects) | |
- Google Cloud team for providing access to TPU's | |